Cardiovascular disease (CVD) is responsible for one third of all deaths in the United States, with the estimated costs anticipated to increase from $500 billion to $1,200 billion between 2015 and 2030. Given the societal burden of CVD, considerable attention has been directed at major risk factors for CVD. Recognition, understanding and widespread ascertainment of additional actionable CVD risk factors is necessary. Greater exercise capacity (e.g. cardiorespiratory fitness) is increasingly recognized to decrease the burden of chronic diseases, promote cardiovascular health, improve quality of life, and delay CVD and mortality. Although fitness has been shown to be among the most potent predictors of future CVD and overall health outcomes, it is currently one of the only major risk factors that is not routinely and regularly assessed in either general or specialized clinical settings. Beyond permitting quantification of fitness, brief (~10min) exposure to exercise can also unmask early forms of CVD. We and others have shown that simple measurements of heart rate and blood pressure during exercise in population studies are of incremental prognostic value over the same measurements made at rest. Recent technological advances now permit measurement of a broad array of circulating metabolites and gas exchange patterns that reflect the complex metabolic responses to exercise. The central hypothesis of this proposal is that precise measurements of metabolic responses to exercise through cardiopulmonary exercise testing (CPET) combined with metabolite profiling during exercise will relate to clinical and genetic traits as well as subclinical CVD, and will be of incremental value beyond standard CV risk factor assessment (in the resting state) for predicting future CVD and cardiometabolic disease. Aim 1 will comprehensively determine how standard risk factors, life-style measures (including precise accelerometry-based physical activity measures), genetic variation and familial traits relate to metabolic responses to exercise, as measured by changes in gas exchange variables and metabolite levels in response to incremental exercise. Aim 2 will determine how previously ascertained subclinical disease measures (conduit artery stiffness, coronary artery calcium, ventricular hypertrophy) relate to metabolic responses to exercise. Aim 3 will determine whether easily acquired CPET gas exchange variables and changes in circulating metabolites in response to exercise will incrementally predict future cardiometabolic and CVD outcomes in the Framingham Heart Study and in a separate referral cohort. Overall, our proposal will help identify and characterize the spectrum of metabolic changes during exercise in the community, and assess their cross-sectional correlates and long-term prognostic significance. We hope to identify a minimally invasive means to test CV and metabolic reserve capacity that will identify and refine risk factors that can be targeted for interventions to prevet CVD.